Answers:
The data distribution of table among AMPs is called Skew Factor . Generally For Non-Unique PI we get duplicate values so the more duplicate vales we get more the data have same row hash so all the same data will come to same amp, it makes data distribution inequality,One amp will store more data and other amp stores less amount of data, when we are accessing full table,
The amp which is having more data will take longer time and makes other amps waiting which leads processing wastage In this situation (unequal distribution of data)we get Skew Factor HighFor this type of tables we should avoid full table scans.
ex:AMP0 AMP110000(10%) 9000000(90%)in this situation skew factor is very high 90%
The data distribution of table among AMPs is called Skew Factor . Generally For Non-Unique PI we get duplicate values so the more duplicate vales we get more the data have same row hash so all the same data will come to same amp, it makes data distribution inequality,One amp will store more data and other amp stores less amount of data, when we are accessing full table,
The amp which is having more data will take longer time and makes other amps waiting which leads processing wastage In this situation (unequal distribution of data)we get Skew Factor HighFor this type of tables we should avoid full table scans.
ex:AMP0 AMP110000(10%) 9000000(90%)in this situation skew factor is very high 90%
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